Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 759 806 445 784 315 224 526 429 825 76 841 595 880 171 403 473 845 298 251 663
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 806 403 663 759 224 595 76 784 526 429 841 315 171 845 880 NA 445 NA 298 251 473 825 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 4 4 2 2 5 4 2 5 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "d" "v" "a" "p" "o" "Z" "S" "H" "C" "O"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
integer(0)
which( manyNumbersWithNA > 900 )
integer(0)
which( is.na( manyNumbersWithNA ) )
[1] 16 18 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
integer(0)
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
integer(0)
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
integer(0)
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "Z" "S" "H" "C" "O"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "d" "v" "a" "p" "o"
manyNumbers %in% 300:600
[1] FALSE FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE FALSE
[18] FALSE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 3 5 7 8 12 15 16
sum( manyNumbers %in% 300:600 )
[1] 7
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "small" "large" "large" "small" "large" "small" "large" "large" "small" "large" "small" "small"
[14] "large" "large" NA "small" NA "small" "small" "small" "large" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "small" "large" "large" "small" "large" "small" "large" "large" "small"
[11] "large" "small" "small" "large" "large" "UNKNOWN" "small" "UNKNOWN" "small" "small"
[21] "small" "large" "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 806 0 663 759 0 595 0 784 526 0 841 0 0 845 880 NA 0 NA 0 0 0 825 NA
unique( duplicatedNumbers )
[1] 3 4 2 5
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 4 2 5
duplicated( duplicatedNumbers )
[1] FALSE FALSE TRUE FALSE TRUE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 15
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 880
which.min( manyNumbersWithNA )
[1] 7
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 76
range( manyNumbersWithNA, na.rm = TRUE )
[1] 76 880
manyNumbersWithNA
[1] 806 403 663 759 224 595 76 784 526 429 841 315 171 845 880 NA 445 NA 298 251 473 825 NA
sort( manyNumbersWithNA )
[1] 76 171 224 251 298 315 403 429 445 473 526 595 663 759 784 806 825 841 845 880
sort( manyNumbersWithNA, na.last = TRUE )
[1] 76 171 224 251 298 315 403 429 445 473 526 595 663 759 784 806 825 841 845 880 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 880 845 841 825 806 784 759 663 595 526 473 445 429 403 315 298 251 224 171 76 NA NA NA
manyNumbersWithNA[1:5]
[1] 806 403 663 759 224
order( manyNumbersWithNA[1:5] )
[1] 5 2 3 4 1
rank( manyNumbersWithNA[1:5] )
[1] 5 2 3 4 1
sort( mixedLetters )
[1] "a" "C" "d" "H" "o" "O" "p" "S" "v" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 8.5 10.0 8.5 2.0 4.0 6.0 6.0 2.0 6.0 2.0
rank( manyDuplicates, ties.method = "min" )
[1] 8 10 8 1 4 5 5 1 5 1
rank( manyDuplicates, ties.method = "random" )
[1] 9 10 8 3 4 5 6 2 7 1
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -0.15909255 -0.18501522 1.68895313
[9] 0.50640422 1.94035697 -0.07700514 1.26848332 0.46908529 0.05367367 0.70700205
round( v, 0 )
[1] -1 0 0 0 1 0 0 2 1 2 0 1 0 0 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.2 -0.2 1.7 0.5 1.9 -0.1 1.3 0.5 0.1 0.7
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.16 -0.19 1.69 0.51 1.94 -0.08 1.27 0.47 0.05 0.71
floor( v )
[1] -1 -1 0 0 1 -1 -1 1 0 1 -1 1 0 0 0
ceiling( v )
[1] -1 0 0 1 1 0 0 2 1 2 0 2 1 1 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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